Monitoramento da qualidade das ásguas de chuvas conforme a atuação dos sistemas sinóticos na cidade de Natal/RN

Acid rain is a major assault on the environment, a consequence of burning fossil fuels and industrial pollutants the basis of sulfur dioxide released into the atmosphere. The objective of this research was to monitor and analyze changes in water quality of rain in the city of Natal, seeking to investigate the influence of quality on a local, regional and global, in addition to possible effects of this quality in the local landscape. Data collection was performed from December 2005 to December 2007. We used techniques of nefanálise in identifying systems sinóticos, field research in the search for possible effects of acid rain on the landscape, and collect and analyze data of precipitation and its degree of acidity. Used descriptive statistics (standard deviation and coefficient of variation) used to monitor the behavior of chemical precipitation, and monitoring of errors in measurements of pH, level of confidence, Normalized distribution of Gauss, confidence intervals, analysis of variance ANOVA were also used. Main results presented as a variation of pH between 5,021 and 6,836, with an average standard deviation of 5,958 and 0,402, showing that the average may represent the sample. Thus, we can infer that, according to the CONAMA Resolution 357 (the index for fresh water acidity should be between 6.0 and 9.0), the precipitation of Natal / RN is slightly acidic. It appears that the intertropical convergence zone figures showed the most acidic among the systems analyzed sinóticos, taking its average value of pH of 5,617, which means an acid value now, with a standard deviation of 0,235 and the coefficient of variation of 4,183% which shows that the average may represent the sample. Already in field research and found several places that suffer strongly the action of acid rain. However, the results are original and need further investigation, including the use of new methodologies

Aplicação da retroanálise na identificação da parcela devida à fluência do concreto da perda de protensão de vigas pré-moldadas de pontes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Identificação de funções de transferência de ordem fracionária utilizando como entrada um degrau

Pós-graduação em Engenharia Elétrica - FEIS

Caracterização experimental de sistemas mecânicos com comportamento não-linear

Pós-graduação em Engenharia Mecânica - FEIS

Design of neuro-fuzzy models by evolutionary and gradient-based algorithms

All systems found in nature exhibit, with different degrees, a nonlinear behavior. To emulate this behavior, classical systems identification techniques use, typically, linear models, for mathematical simplicity. Models inspired by biological principles (artificial neural networks) and linguistically motivated (fuzzy systems), due to their universal approximation property, are becoming alternatives to classical mathematical models. In systems identification, the design of this type of models is an iterative process, requiring, among other steps, the need to identify the model structure, as well as the estimation of the model parameters. This thesis addresses the applicability of gradient-basis algorithms for the parameter estimation phase, and the use of evolutionary algorithms for model structure selection, for the design of neuro-fuzzy systems, i.e., models that offer the transparency property found in fuzzy systems, but use, for their design, algorithms introduced in the context of neural networks. A new methodology, based on the minimization of the integral of the error, and exploiting the parameter separability property typically found in neuro-fuzzy systems, is proposed for parameter estimation. A recent evolutionary technique (bacterial algorithms), based on the natural phenomenon of microbial evolution, is combined with genetic programming, and the resulting algorithm, bacterial programming, advocated for structure determination. Different versions of this evolutionary technique are combined with gradient-based algorithms, solving problems found in fuzzy and neuro-fuzzy design, namely incorporation of a-priori knowledge, gradient algorithms initialization and model complexity reduction.

Sincronização em neurônios de Hindmarsh-Rose

A sincronização, como comportamento cooperativo universal e mecanismo fundamental na natureza, tem sido extensivamente estudada em conexão com inúmeros fenômenos em física, química e biologia [1, 2]. Em particular, a sincronização da atividade neural tem sido observada em diferentes espécies e sob condições fisiológicas distintas [3, 4]. Neste trabalho, estudamos sincronização em neurônios de Hindmarsh-Rose (HR), um modelo de potencial de membrana que representa com fidelidade o comportamento de disparos encontrado em neurônios reais [9, 10]. Iniciamos considerando o caso de um neurônio HR isolado e suas propriedades dinâmicas de geração de pulsos. Em seguida, analisamos o acoplamento entre neurônios em um sistema de dois neurônios, e em redes unidimensionais (HR-1D) e bidimensionais (HR-2D). Nessas arquiteturas, a sincronização dos elementos da rede da origem a um comportamento ordenado, coerente, que está associado não somente à produção de informação biológica [5, 6], mas também às potenciais aplicações em comunicação [7] e identificação de sistemas [8].

Um sistema para estimação da vazão de gás de poços produzindo por Plunger Lift para vaso separador de teste em plataformas de petróleo

This work intends to analyze the behavior of the gas flow of plunger lift wells producing to well testing separators in offshore production platforms to aim a technical procedure to estimate the gas flow during the slug production period. The motivation for this work appeared from the expectation of some wells equipped with plunger lift method by PETROBRAS in Ubarana sea field located at Rio Grande do Norte State coast where the produced fluids measurement is made in well testing separators at the platform. The oil artificial lift method called plunger lift is used when the available energy of the reservoir is not high enough to overcome all the necessary load losses to lift the oil from the bottom of the well to the surface continuously. This method consists, basically, in one free piston acting as a mechanical interface between the formation gas and the produced liquids, greatly increasing the well s lifting efficiency. A pneumatic control valve is mounted at the flow line to control the cycles. When this valve opens, the plunger starts to move from the bottom to the surface of the well lifting all the oil and gas that are above it until to reach the well test separator where the fluids are measured. The well test separator is used to measure all the volumes produced by the well during a certain period of time called production test. In most cases, the separators are designed to measure stabilized flow, in other words, reasonably constant flow by the use of level and pressure electronic controllers (PLC) and by assumption of a steady pressure inside the separator. With plunger lift wells the liquid and gas flow at the surface are cyclical and unstable what causes the appearance of slugs inside the separator, mainly in the gas phase, because introduce significant errors in the measurement system (e.g.: overrange error). The flow gas analysis proposed in this work is based on two mathematical models used together: i) a plunger lift well model proposed by Baruzzi [1] with later modifications made by Bolonhini [2] to built a plunger lift simulator; ii) a two-phase separator model (gas + liquid) based from a three-phase separator model (gas + oil + water) proposed by Nunes [3]. Based on the models above and with field data collected from the well test separator of PUB-02 platform (Ubarana sea field) it was possible to demonstrate that the output gas flow of the separator can be estimate, with a reasonable precision, from the control signal of the Pressure Control Valve (PCV). Several models of the System Identification Toolbox from MATLAB® were analyzed to evaluate which one better fit to the data collected from the field. For validation of the models, it was used the AIC criterion, as well as a variant of the cross validation criterion. The ARX model performance was the best one to fit to the data and, this way, we decided to evaluate a recursive algorithm (RARX) also with real time data. The results were quite promising that indicating the viability to estimate the output gas flow rate from a plunger lift well producing to a well test separator, with the built-in information of the control signal to the PCV

Metodologia para re-sintonia de controladores PID industriais

The present work has as objective to present a method of project and implementation of controllers PID, based on industrial instrumentation. An automatic system of auto-tunning of controllers PID will be presented, for systems of first and second order. The software presented in this work is applied in controlled plants by PID controllers implemented in a CLP. Software is applied to make the auto-tunning of the parameters of controller PID of plants that need this tunning. Software presents two stages, the first one is the stage of identification of the system using the least square recursive algorithm and the second is the stage of project of the parameters of controller PID using the root locus algorithm. An important fact of this work is the use of industrial instrumentation for the accomplishment of the experiments. The experiments had been carried through in controlled real plants for controllers PID implemented in the CLP. Thus has not only one resulted obtained with theoreticians experiments made with computational programs, and yes resulted obtained of real systems. The experiments had shown good results gotten with developed software

Implementação de um sistema embarcado aplicado ao controle de pressão arterial

Hypertension is a dangerous disease that can cause serious harm to a patient health. In some situations the necessity to control this pressure is even greater, as in surgical procedures and post-surgical patients. To decrease the chances of a complication, it is necessary to reduce blood pressure as soon as possible. Continuous infusion of vasodilators drugs, such as sodium nitroprusside (SNP), rapidly decreased blood pressure in most patients, avoiding major problems. Maintaining the desired blood pressure requires constant monitoring of arterial blood pressure and frequently adjusting the drug infusion rate. Manual control of arterial blood pressure by clinical personnel is very demanding, time consuming and, as a result, sometimes of poor quality. Thus, the aim of this work is the design and implementation of a database of tuned controllers based on patients models, in order to find a suitable PID to be embedded in a Programmable Integrated Circuit (PIC), which has a smaller cost, smaller size and lower power consumption. For best results in controlling the blood pressure and choosing the adequate controller, tuning algorithms, system identification techniques and Smith predictor are used. This work also introduces a monitoring system to assist in detecting anomalies and optimize the process of patient care.

Estudo e implementação de um controlador preditivo generalizado bilinear compensado adaptativo

The present work presents the study and implementation of an adaptive bilinear compensated generalized predictive controller. This work uses conventional techniques of predictive control and includes techniques of adaptive control for better results. In order to solve control problems frequently found in the chemical industry, bilinear models are considered to represent the dynamics of the studied systems. Bilinear models are simpler than general nonlinear model, however it can to represent the intrinsic not-linearities of industrial processes. The linearization of the model, by the approach to time step quasilinear , is used to allow the application of the equations of the generalized predictive controller (GPC). Such linearization, however, generates an error of prediction, which is minimized through a compensation term. The term in study is implemented in an adaptive form, due to the nonlinear relationship between the input signal and the prediction error.Simulation results show the efficiency of adaptive predictive bilinear controller in comparison with the conventional.

Predição da incrustação em um trocador de calor baseada em redes neurais artificiais

A serious problem that affects an oil refinery s processing units is the deposition of solid particles or the fouling on the equipments. These residues are naturally present on the oil or are by-products of chemical reactions during its transport. A fouled heat exchanger loses its capacity to adequately heat the oil, needing to be shut down periodically for cleaning. Previous knowledge of the best period to shut down the exchanger may improve the energetic and production efficiency of the plant. In this work we develop a system to predict the fouling on a heat exchanger from the Potiguar Clara Camarão Refinery, based on data collected in a partnership with Petrobras. Recurrent Neural Networks are used to predict the heat exchanger s flow in future time. This variable is the main indicator of fouling, because its value decreases gradually as the deposits on the tubes reduce their diameter. The prediction could be used to tell when the flow will have decreased under an acceptable value, indicating when the exchanger shutdown for cleaning will be needed

Uma abordagem neural para estimação de conjugado em motores de indução

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Detecção de falhas estruturais usando sensores e atuadores piezelétricos e algoritmos genéticos

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modelagem de séries de monitoramento de nível freático em área de afloramento do sistema aquífero guarani (sag) sob influência de diferentes usos agrícolas da terra

Pós-graduação em Agronomia (Irrigação e Drenagem) - FCA